Recent findings reveal that 80% of AI decision makers are expressing worries about data privacy and security in their organizations. A study conducted by Coleman Parkes Research and sponsored by data analytics firm SAS surveyed 300 US GenAI strategy or data analytics decision makers, shedding light on major areas of investment and the obstacles hindering organizations from maximizing the potential of generative AI.
Marinela Profi, strategic AI advisor at SAS, emphasized the importance of strategic planning and technology integration for leveraging generative AI effectively. Profi stated, “GenAI should be treated as an ideal contributor to hyper-automation and the acceleration of existing processes and systems rather than the new shiny toy.”
The study identified key stumbling blocks in GenAI implementation:
- Trust and Compliance: Only 1 in 10 organizations has a reliable system to measure bias and privacy risk in large language models (LLMs). Additionally, 93% lack a comprehensive governance framework for GenAI, posing risks of noncompliance with regulations.
- Integration: Organizations encounter compatibility issues when integrating GenAI with existing systems and processes.
- Talent and Skills: There’s a shortage of in-house GenAI talent, with HR departments struggling to find suitable hires.
- Cost Predictability: Leaders face prohibitive direct and indirect costs associated with using LLMs, including private knowledge preparation, training, and ModelOps management.
Profi emphasized the importance of identifying real-world use cases that deliver high value and solve human needs sustainably and at scale. She highlighted the study’s role in helping organizations invest wisely and stay resilient in a rapidly evolving AI landscape.
These insights were unveiled at SAS Innovate in Las Vegas, SAS Software’s AI and analytics conference, where business leaders, technical users, and SAS partners gathered to explore the latest trends and innovations in AI and analytics.
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